Specify task/support variables as data

prosper_nn/models/hcnn_compressed/hcnn_cell_compressed.py

@@ -103,24 +103,24 @@ def __init__(
     def forward(
         self,
         state: torch.Tensor,
-        task: Optional[torch.Tensor] = None,
-        support: Optional[torch.Tensor] = None,
+        observation_task: Optional[torch.Tensor] = None,
+        observation_support: Optional[torch.Tensor] = None,
     ):
         """
         Parameters
         ----------
         state : torch.Tensor
             The previous state of the HCNN. shape = (batch_size, n_state_neurons)
-        task : torch.Tensor
-            The task is the data for the given timestamp which should be predicted from supports.
+        observation_task : torch.Tensor
+            The observation_task is the data for the given timestamp which should be predicted from supports.
             It has the
             shape = (batchsize, n_features_task).
             It is an optional variable. If no variable is given,
             the observation is not subtracted
             from the expectation to create the output variable.
             Additionally, no teacher forcing is applied on the state vector.
-        support : torch.Tensor
-            The support is the data for the given timestamp which is compressed and then used to learn task.
+        observation_support : torch.Tensor
+            The observation_support is the data for the given timestamp which is compressed and then used to learn observation_task.
             It has the
             shape = (batchsize, n_features_sup).
             It is an optional variable. If no variable is given,
@@ -134,18 +134,18 @@ def forward(
         state : torch.Tensor
             The updated state of the HCNN.
         output_task: torch.Tensor
-            The output of the HCNN Cell. If a task is given,
-            this output is calculated by the expectation_task minus the task.
-            If no task is given, the output is equal to the expectation.
+            The output of the HCNN Cell. If a observation_task is given,
+            this output is calculated by the expectation_task minus the observation_task.
+            If no observation_task is given, the output is equal to the expectation.
         """
 
         expectation_task = torch.mm(state, self.eye_task.T)
         expectation_support = torch.mm(state, self.eye_support.T)
 
-        if task is not None and support is not None:
-            support_compressed = self.E(support)
+        if observation_task is not None and observation_support is not None:
+            support_compressed = self.E(observation_support)
 
-            output_task = expectation_task - task
+            output_task = expectation_task - observation_task
             output_support = expectation_support - support_compressed
 
             teacher_forcing_task = torch.mm(
@@ -159,8 +159,8 @@ def forward(
                 state - teacher_forcing_task - teacher_forcing_support
             )
 
-        elif xor(task is None, support is None):  # XOR only one of them is set
-            self.set_task_and_support_error(task, support)
+        elif xor(observation_task is None, observation_support is None):  # XOR only one of them is set
+            self.set_task_and_support_error(observation_task, observation_support)
 
         else:  # Forecasts
             output_task = expectation_task
@@ -190,21 +190,21 @@ def set_teacher_forcing(self, teacher_forcing: float) -> None:
         self.teacher_forcing = teacher_forcing
         self.ptf_dropout.p = 1 - teacher_forcing
 
-    def set_task_and_support_error(self, task, support) -> None:
+    def set_task_and_support_error(self, observation_task, observation_support) -> None:
         """
-        The task and support tensors should either both be set or both be not set.
+        The observation_task and observation_support tensors should either both be set or both be not set.
         This is used to check and throw the error if either of them is empty and reminds to set that.
 
 
         Parameters
         ----------
-        task, support
+        observation_task, observation_support
 
         Returns
         -------
         None
         """
-        if task is None:
-            raise ValueError("Task is empty and please set it")
-        elif support is None:
-            raise ValueError("Support is empty and please set it")
+        if observation_task is None:
+            raise ValueError("observation_task is empty and please set it")
+        elif observation_support is None:
+            raise ValueError("observation_support is empty and please set it")